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| import gradio as gr | |
| import os | |
| from acrcloud.recognizer import ACRCloudRecognizer | |
| import tempfile | |
| import shutil | |
| import json | |
| # Retrieve ACRCloud credentials from environment variables | |
| acr_access_key = os.environ.get('ACR_ACCESS_KEY') | |
| acr_access_secret = os.environ.get('ACR_ACCESS_SECRET') | |
| acr_host = 'identify-ap-southeast-1.acrcloud.com' # os.environ.get('ACR_HOST', 'eu-west-1.api.acrcloud.com') | |
| # ACRCloud recognizer configuration | |
| config = { | |
| 'host': acr_host, | |
| 'access_key': acr_access_key, | |
| 'access_secret': acr_access_secret, | |
| 'timeout': 10 # seconds | |
| } | |
| # Initialize ACRCloud recognizer | |
| acr = ACRCloudRecognizer(config) | |
| def identify_audio(file): | |
| # Gradio provides a file object, and file.name contains the path | |
| file_path = file.name # Gradio file object already provides a file path | |
| # Get the duration of the audio file in milliseconds | |
| duration_ms = int(acr.get_duration_ms_by_file(file_path)) | |
| results = [] | |
| # Process audio in 10-second chunks | |
| for i in range(0, duration_ms // 1000, 10): | |
| res = acr.recognize_by_file(file_path, i, 10) | |
| results.append(f"**Time {i}s**: {res.strip()}") | |
| # Full recognition result | |
| full_result = acr.recognize_by_file(file_path, 0) | |
| # Recognize using file buffer | |
| with open(file_path, 'rb') as f: | |
| buf = f.read() | |
| buffer_result = acr.recognize_by_filebuffer(buf, 0) | |
| # Convert JSON results to dictionary | |
| full_result_dict = json.loads(full_result) | |
| buffer_result_dict = json.loads(buffer_result) | |
| # Format the results as markdown | |
| result_md = f""" | |
| ### **Partial Results**: | |
| {'\n'.join(results)} | |
| ### **Full Result**: | |
| - **Track**: {full_result_dict['metadata']['music'][0]['title']} | |
| - **Artist**: {full_result_dict['metadata']['music'][0]['artists'][0]['name']} | |
| - **Album**: {full_result_dict['metadata']['music'][0]['album']['name']} | |
| - **Release Date**: {full_result_dict['metadata']['music'][0]['release_date']} | |
| - **Score**: {full_result_dict['metadata']['music'][0]['score']}% | |
| ### **Buffer Result**: | |
| - **Track**: {buffer_result_dict['metadata']['music'][0]['title']} | |
| - **Artist**: {buffer_result_dict['metadata']['music'][0]['artists'][0]['name']} | |
| - **Album**: {buffer_result_dict['metadata']['music'][0]['album']['name']} | |
| - **Release Date**: {buffer_result_dict['metadata']['music'][0]['release_date']} | |
| - **Score**: {buffer_result_dict['metadata']['music'][0]['score']}% | |
| """ | |
| return gr.Markdown(result_md) | |
| # Create Gradio interface | |
| iface = gr.Interface( | |
| fn=identify_audio, | |
| inputs=gr.File(label="Upload Audio File"), | |
| outputs=gr.Markdown(label="Audio Metadata"), | |
| title="Audio Search by File", | |
| description="Upload an audio file to identify it using ACRCloud." | |
| ) | |
| # Launch the Gradio interface | |
| iface.launch() | |